Neural Network
Neural networks are computational models inspired by the structure and function of the brain, primarily aimed at approximating complex functions and solving diverse problems through learning from data. Current research emphasizes improving efficiency and robustness, exploring novel architectures like sinusoidal neural fields and hybrid models combining neural networks with radial basis functions, as well as developing methods for understanding and manipulating the internal representations learned by these networks, such as through hyper-representations of network weights. These advancements are driving progress in various fields, including computer vision, natural language processing, and scientific modeling, by enabling more accurate, efficient, and interpretable AI systems.
Papers
Emergent field theories from neural networks
Vitaly Vanchurin
Exploring the loss landscape of regularized neural networks via convex duality
Sungyoon Kim, Aaron Mishkin, Mert Pilanci
Maritime Search and Rescue Missions with Aerial Images: A Survey
Juan P. Martinez-Esteso, Francisco J. Castellanos, Jorge Calvo-Zaragoza, Antonio Javier Gallego
SoundSil-DS: Deep Denoising and Segmentation of Sound-field Images with Silhouettes
Risako Tanigawa, Kenji Ishikawa, Noboru Harada, Yasuhiro Oikawa
Training Neural Networks as Recognizers of Formal Languages
Alexandra Butoi, Ghazal Khalighinejad, Anej Svete, Josef Valvoda, Ryan Cotterell, Brian DuSell
Randomized Forward Mode Gradient for Spiking Neural Networks in Scientific Machine Learning
Ruyin Wan, Qian Zhang, George Em Karniadakis
Generative Feature Training of Thin 2-Layer Networks
Johannes Hertrich, Sebastian Neumayer
Evolving Efficient Genetic Encoding for Deep Spiking Neural Networks
Wenxuan Pan, Feifei Zhao, Bing Han, Haibo Tong, Yi Zeng
MP-PINN: A Multi-Phase Physics-Informed Neural Network for Epidemic Forecasting
Thang Nguyen, Dung Nguyen, Kha Pham, Truyen Tran
A Text Classification Model Combining Adversarial Training with Pre-trained Language Model and neural networks: A Case Study on Telecom Fraud Incident Texts
Liu Zhuoxian, Shi Tuo, Hu Xiaofeng
Precision Glass Thermoforming Assisted by Neural Networks
Yuzhou Zhang, Mohan Hua, Haihui Ruan
On the Principles of ReLU Networks with One Hidden Layer
Changcun Huang
Multi-Dimensional Reconfigurable, Physically Composable Hybrid Diffractive Optical Neural Network
Ziang Yin, Yu Yao, Jeff Zhang, Jiaqi Gu
Learning Subsystem Dynamics in Nonlinear Systems via Port-Hamiltonian Neural Networks
G.J.E. van Otterdijk, S. Moradi, S. Weiland, R. Tóth, N.O. Jaensson, M. Schoukens